Overview

Dataset statistics

Number of variables7
Number of observations780
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory27.4 KiB
Average record size in memory36.0 B

Variable types

Numeric7

Alerts

hurs is highly overall correlated with huss and 3 other fieldsHigh correlation
huss is highly overall correlated with hurs and 2 other fieldsHigh correlation
month is highly overall correlated with tasHigh correlation
pr is highly overall correlated with hurs and 1 other fieldsHigh correlation
psl is highly overall correlated with hurs and 3 other fieldsHigh correlation
tas is highly overall correlated with hurs and 3 other fieldsHigh correlation
psl has unique valuesUnique
pr has unique valuesUnique
huss has unique valuesUnique
hurs has unique valuesUnique
clt has unique valuesUnique

Reproduction

Analysis started2023-12-14 15:32:25.909157
Analysis finished2023-12-14 15:32:31.259382
Duration5.35 seconds
Software versionydata-profiling vv4.6.3
Download configurationconfig.json

Variables

tas
Real number (ℝ)

HIGH CORRELATION 

Distinct779
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean284.8193
Minimum279.93481
Maximum291.09164
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size9.1 KiB
2023-12-14T15:32:31.351603image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum279.93481
5-th percentile281.18351
Q1282.46478
median284.12411
Q3287.32218
95-th percentile289.61489
Maximum291.09164
Range11.15683
Interquartile range (IQR)4.8574066

Descriptive statistics

Standard deviation2.7831063
Coefficient of variation (CV)0.0097714807
Kurtosis-1.0828869
Mean284.8193
Median Absolute Deviation (MAD)2.1204681
Skewness0.38645178
Sum222159.06
Variance7.7456808
MonotonicityNot monotonic
2023-12-14T15:32:31.504169image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
288.7102966 2
 
0.3%
283.4649658 1
 
0.1%
286.0784302 1
 
0.1%
283.141571 1
 
0.1%
280.3231812 1
 
0.1%
282.0586548 1
 
0.1%
281.1917114 1
 
0.1%
283.5515747 1
 
0.1%
286.4076843 1
 
0.1%
287.453186 1
 
0.1%
Other values (769) 769
98.6%
ValueCountFrequency (%)
279.9348145 1
0.1%
280.1912537 1
0.1%
280.20047 1
0.1%
280.2106934 1
0.1%
280.3207703 1
0.1%
280.3231812 1
0.1%
280.3589783 1
0.1%
280.4697571 1
0.1%
280.5248718 1
0.1%
280.5676575 1
0.1%
ValueCountFrequency (%)
291.0916443 1
0.1%
290.9079895 1
0.1%
290.7064819 1
0.1%
290.683075 1
0.1%
290.6772766 1
0.1%
290.4032898 1
0.1%
290.3586426 1
0.1%
290.3175049 1
0.1%
290.3087769 1
0.1%
290.2770386 1
0.1%

psl
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct780
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean101728.73
Minimum98537.086
Maximum103564.34
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size9.1 KiB
2023-12-14T15:32:31.648495image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum98537.086
5-th percentile99809.104
Q1101158.61
median101914.89
Q3102482.2
95-th percentile103005.04
Maximum103564.34
Range5027.2578
Interquartile range (IQR)1323.5879

Descriptive statistics

Standard deviation971.87341
Coefficient of variation (CV)0.0095535784
Kurtosis0.13109075
Mean101728.73
Median Absolute Deviation (MAD)646.30078
Skewness-0.74731654
Sum79348410
Variance944537.88
MonotonicityNot monotonic
2023-12-14T15:32:31.791340image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
101614.7578 1
 
0.1%
102137.1094 1
 
0.1%
100813.0312 1
 
0.1%
101908.8359 1
 
0.1%
100351.4688 1
 
0.1%
102514.7344 1
 
0.1%
101466.9922 1
 
0.1%
102675.5547 1
 
0.1%
101698.1484 1
 
0.1%
102935.4531 1
 
0.1%
Other values (770) 770
98.7%
ValueCountFrequency (%)
98537.08594 1
0.1%
98683.89844 1
0.1%
98707.76562 1
0.1%
98757.25 1
0.1%
98935.48438 1
0.1%
99025.33594 1
0.1%
99038.91406 1
0.1%
99053.46875 1
0.1%
99105.70312 1
0.1%
99144.96875 1
0.1%
ValueCountFrequency (%)
103564.3438 1
0.1%
103454.6562 1
0.1%
103398.9219 1
0.1%
103380.0859 1
0.1%
103369.1172 1
0.1%
103348.4922 1
0.1%
103299.9062 1
0.1%
103286.3828 1
0.1%
103284.75 1
0.1%
103260.3047 1
0.1%

pr
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct780
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.3483474 × 10-5
Minimum2.8320135 × 10-6
Maximum0.00011424207
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size9.1 KiB
2023-12-14T15:32:31.935367image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum2.8320135 × 10-6
5-th percentile9.3385931 × 10-6
Q12.4118432 × 10-5
median4.0769477 × 10-5
Q36.1006719 × 10-5
95-th percentile8.8674127 × 10-5
Maximum0.00011424207
Range0.00011141005
Interquartile range (IQR)3.6888287 × 10-5

Descriptive statistics

Standard deviation2.4587978 × 10-5
Coefficient of variation (CV)0.56545571
Kurtosis-0.61601049
Mean4.3483474 × 10-5
Median Absolute Deviation (MAD)1.8836834 × 10-5
Skewness0.45375371
Sum0.033917109
Variance6.0456867 × 10-10
MonotonicityNot monotonic
2023-12-14T15:32:32.092563image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7.20359094 × 10-51
 
0.1%
4.622890992 × 10-51
 
0.1%
6.053136894 × 10-51
 
0.1%
5.692386185 × 10-51
 
0.1%
7.679591363 × 10-51
 
0.1%
2.000384302 × 10-51
 
0.1%
2.500817391 × 10-51
 
0.1%
1.262735532 × 10-51
 
0.1%
3.408694465 × 10-51
 
0.1%
1.634664659 × 10-51
 
0.1%
Other values (770) 770
98.7%
ValueCountFrequency (%)
2.832013479 × 10-61
0.1%
3.692265409 × 10-61
0.1%
3.921470579 × 10-61
0.1%
3.983047918 × 10-61
0.1%
4.63321021 × 10-61
0.1%
5.273077477 × 10-61
0.1%
5.321352546 × 10-61
0.1%
5.432638773 × 10-61
0.1%
5.468837571 × 10-61
0.1%
5.647321814 × 10-61
0.1%
ValueCountFrequency (%)
0.000114242066 1
0.1%
0.0001048226695 1
0.1%
0.0001044659948 1
0.1%
0.0001034467205 1
0.1%
0.0001032211803 1
0.1%
0.0001030658532 1
0.1%
0.0001028907645 1
0.1%
0.0001026540631 1
0.1%
0.0001025182501 1
0.1%
0.0001022205033 1
0.1%

huss
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct780
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0072285014
Minimum0.0044479137
Maximum0.011324178
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size9.1 KiB
2023-12-14T15:32:32.243146image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum0.0044479137
5-th percentile0.0052013822
Q10.0058258212
median0.0066318011
Q30.0086952534
95-th percentile0.010207848
Maximum0.011324178
Range0.0068762647
Interquartile range (IQR)0.0028694322

Descriptive statistics

Standard deviation0.0016670425
Coefficient of variation (CV)0.23062076
Kurtosis-0.96349496
Mean0.0072285014
Median Absolute Deviation (MAD)0.0010689879
Skewness0.56080741
Sum5.6382311
Variance2.7790306 × 10-6
MonotonicityNot monotonic
2023-12-14T15:32:32.396151image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.006408142857 1
 
0.1%
0.009087393992 1
 
0.1%
0.00571279414 1
 
0.1%
0.005855915137 1
 
0.1%
0.006268389057 1
 
0.1%
0.004447913729 1
 
0.1%
0.005899365991 1
 
0.1%
0.00524146948 1
 
0.1%
0.006804367527 1
 
0.1%
0.008111521602 1
 
0.1%
Other values (770) 770
98.7%
ValueCountFrequency (%)
0.004447913729 1
0.1%
0.004665129818 1
0.1%
0.004682254512 1
0.1%
0.004700215533 1
0.1%
0.004796852358 1
0.1%
0.004885761999 1
0.1%
0.004890537355 1
0.1%
0.004894543439 1
0.1%
0.004921589047 1
0.1%
0.004926856607 1
0.1%
ValueCountFrequency (%)
0.01132417843 1
0.1%
0.0111496076 1
0.1%
0.0111465808 1
0.1%
0.01107975468 1
0.1%
0.01099363342 1
0.1%
0.0108422609 1
0.1%
0.01082422584 1
0.1%
0.01081577782 1
0.1%
0.01073484402 1
0.1%
0.01071147248 1
0.1%

hurs
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct780
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean83.012731
Minimum70.805511
Maximum95.053535
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size9.1 KiB
2023-12-14T15:32:32.552608image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum70.805511
5-th percentile74.880487
Q178.668709
median82.194614
Q387.584019
95-th percentile92.204064
Maximum95.053535
Range24.248024
Interquartile range (IQR)8.9153099

Descriptive statistics

Standard deviation5.5539489
Coefficient of variation (CV)0.066904784
Kurtosis-0.94723421
Mean83.012731
Median Absolute Deviation (MAD)4.2718964
Skewness0.22373362
Sum64749.93
Variance30.846346
MonotonicityNot monotonic
2023-12-14T15:32:32.710477image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
82.14170074 1
 
0.1%
85.3074646 1
 
0.1%
70.80551147 1
 
0.1%
78.67189789 1
 
0.1%
81.06030273 1
 
0.1%
71.37632751 1
 
0.1%
82.56732178 1
 
0.1%
79.28140259 1
 
0.1%
86.67138672 1
 
0.1%
86.90856934 1
 
0.1%
Other values (770) 770
98.7%
ValueCountFrequency (%)
70.80551147 1
0.1%
70.98133087 1
0.1%
71.35748291 1
0.1%
71.37632751 1
0.1%
71.74607849 1
0.1%
72.82809448 1
0.1%
72.91634369 1
0.1%
73.09040833 1
0.1%
73.1255188 1
0.1%
73.43793488 1
0.1%
ValueCountFrequency (%)
95.05353546 1
0.1%
94.69850922 1
0.1%
94.53808594 1
0.1%
94.47307587 1
0.1%
94.44455719 1
0.1%
94.43530273 1
0.1%
94.16853333 1
0.1%
94.07239532 1
0.1%
94.01081848 1
0.1%
93.86116028 1
0.1%

clt
Real number (ℝ)

UNIQUE 

Distinct780
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean89.673069
Minimum68.238106
Maximum99.411186
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size9.1 KiB
2023-12-14T15:32:32.855511image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum68.238106
5-th percentile81.120158
Q186.748985
median90.372433
Q393.152781
95-th percentile96.29702
Maximum99.411186
Range31.17308
Interquartile range (IQR)6.4037952

Descriptive statistics

Standard deviation4.7912846
Coefficient of variation (CV)0.053430585
Kurtosis0.46506959
Mean89.673069
Median Absolute Deviation (MAD)3.2268219
Skewness-0.6610319
Sum69944.994
Variance22.956408
MonotonicityNot monotonic
2023-12-14T15:32:33.003270image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
88.78627777 1
 
0.1%
87.36743164 1
 
0.1%
79.69719696 1
 
0.1%
94.20975494 1
 
0.1%
81.0478363 1
 
0.1%
88.90888977 1
 
0.1%
85.74976349 1
 
0.1%
90.04756165 1
 
0.1%
85.19886017 1
 
0.1%
84.66419983 1
 
0.1%
Other values (770) 770
98.7%
ValueCountFrequency (%)
68.23810577 1
0.1%
72.8895874 1
0.1%
73.00016022 1
0.1%
74.04337311 1
0.1%
75.47214508 1
0.1%
75.52338409 1
0.1%
76.29481506 1
0.1%
76.61385345 1
0.1%
76.61701202 1
0.1%
76.78833771 1
0.1%
ValueCountFrequency (%)
99.41118622 1
0.1%
99.15815735 1
0.1%
99.03217316 1
0.1%
99.02552032 1
0.1%
98.97110748 1
0.1%
98.92603302 1
0.1%
98.72583771 1
0.1%
98.45838928 1
0.1%
98.35521698 1
0.1%
98.00247192 1
0.1%

month
Real number (ℝ)

HIGH CORRELATION 

Distinct12
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.5
Minimum1
Maximum12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size9.1 KiB
2023-12-14T15:32:33.127889image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13.75
median6.5
Q39.25
95-th percentile12
Maximum12
Range11
Interquartile range (IQR)5.5

Descriptive statistics

Standard deviation3.4542675
Coefficient of variation (CV)0.53142577
Kurtosis-1.2168873
Mean6.5
Median Absolute Deviation (MAD)3
Skewness0
Sum5070
Variance11.931964
MonotonicityNot monotonic
2023-12-14T15:32:33.240526image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
1 65
8.3%
2 65
8.3%
3 65
8.3%
4 65
8.3%
5 65
8.3%
6 65
8.3%
7 65
8.3%
8 65
8.3%
9 65
8.3%
10 65
8.3%
Other values (2) 130
16.7%
ValueCountFrequency (%)
1 65
8.3%
2 65
8.3%
3 65
8.3%
4 65
8.3%
5 65
8.3%
6 65
8.3%
7 65
8.3%
8 65
8.3%
9 65
8.3%
10 65
8.3%
ValueCountFrequency (%)
12 65
8.3%
11 65
8.3%
10 65
8.3%
9 65
8.3%
8 65
8.3%
7 65
8.3%
6 65
8.3%
5 65
8.3%
4 65
8.3%
3 65
8.3%

Interactions

2023-12-14T15:32:30.271335image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2023-12-14T15:32:26.063065image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2023-12-14T15:32:26.759067image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2023-12-14T15:32:27.430432image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2023-12-14T15:32:28.113051image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2023-12-14T15:32:28.904160image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2023-12-14T15:32:29.577881image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2023-12-14T15:32:30.365677image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2023-12-14T15:32:26.166198image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2023-12-14T15:32:26.853759image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2023-12-14T15:32:27.527629image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2023-12-14T15:32:28.285665image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2023-12-14T15:32:29.000060image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2023-12-14T15:32:29.677920image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2023-12-14T15:32:30.455931image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2023-12-14T15:32:26.264922image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2023-12-14T15:32:26.942235image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2023-12-14T15:32:27.620641image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2023-12-14T15:32:28.381305image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2023-12-14T15:32:29.093653image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2023-12-14T15:32:29.776370image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2023-12-14T15:32:30.553271image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2023-12-14T15:32:26.367435image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2023-12-14T15:32:27.038610image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2023-12-14T15:32:27.717939image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2023-12-14T15:32:28.485773image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2023-12-14T15:32:29.190903image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2023-12-14T15:32:29.874941image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2023-12-14T15:32:30.652432image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2023-12-14T15:32:26.469460image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2023-12-14T15:32:27.139629image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2023-12-14T15:32:27.819953image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2023-12-14T15:32:28.592135image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2023-12-14T15:32:29.291467image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2023-12-14T15:32:29.978139image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2023-12-14T15:32:30.748014image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2023-12-14T15:32:26.564785image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2023-12-14T15:32:27.237707image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2023-12-14T15:32:27.916899image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2023-12-14T15:32:28.699408image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2023-12-14T15:32:29.384834image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2023-12-14T15:32:30.076249image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2023-12-14T15:32:30.847894image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2023-12-14T15:32:26.664164image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2023-12-14T15:32:27.337755image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2023-12-14T15:32:28.016733image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2023-12-14T15:32:28.805367image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2023-12-14T15:32:29.482354image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2023-12-14T15:32:30.175131image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Correlations

2023-12-14T15:32:33.326530image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
clthurshussmonthprpsltas
clt1.0000.4350.182-0.014-0.3600.4170.099
hurs0.4351.0000.7720.011-0.6870.6920.632
huss0.1820.7721.0000.437-0.4910.6350.976
month-0.0140.0110.4371.0000.0450.1810.543
pr-0.360-0.687-0.4910.0451.000-0.822-0.412
psl0.4170.6920.6350.181-0.8221.0000.588
tas0.0990.6320.9760.543-0.4120.5881.000

Missing values

2023-12-14T15:32:30.977953image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-14T15:32:31.207193image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

taspslprhusshurscltmonth
time
1950-01-15 12:00:00283.464966101614.7578120.0000720.00640882.14170188.7862781
1950-02-14 00:00:00283.164246103564.3437500.0000280.00610281.25833191.5046082
1950-03-15 12:00:00282.670654102712.6718750.0000330.00595781.23825895.6335753
1950-04-15 00:00:00282.740906102592.0156250.0000190.00597581.23300292.0557174
1950-05-15 12:00:00283.769928101906.6093750.0000260.00644881.24726980.9383855
1950-06-15 00:00:00287.731720102829.9531250.0000060.00918890.53995596.2430506
1950-07-15 12:00:00289.170105103108.5234380.0000120.00986887.76881494.9640127
1950-08-15 12:00:00290.358643102972.0937500.0000100.01046586.83622785.8369758
1950-09-15 00:00:00289.400299102499.3984380.0000300.00936581.43563175.4721459
1950-10-15 12:00:00286.500549101889.1093750.0000450.00744177.32511191.02420810
taspslprhusshurscltmonth
time
2014-03-15 12:00:00282.954102101149.9921880.0000750.00649385.62116289.1168593
2014-04-15 00:00:00282.465485101936.4687500.0000360.00589280.98057693.3681264
2014-05-15 12:00:00283.676208102841.1406250.0000160.00656284.02388083.6418005
2014-06-15 00:00:00286.858948102189.0156250.0000190.00874690.44070495.1551826
2014-07-15 12:00:00288.825500102765.4453120.0000330.01002292.25351095.1843957
2014-08-15 12:00:00289.600983103369.1171880.0000060.01014089.39361686.7931828
2014-09-15 00:00:00289.980011102390.7265620.0000560.01032687.59771786.6143499
2014-10-15 12:00:00288.456390101591.1718750.0000530.00882081.44454286.38714610
2014-11-15 00:00:00284.990112100635.4140620.0000790.00669576.89625583.44910411
2014-12-15 12:00:00283.48852599512.2109380.0000650.00629978.95578885.26568612